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Predictors of Tobacco Use among Persons with Mental Illnesses for a Statewide Population

Predictors of Tobacco Use among Persons with Mental Illnesses for a Statewide Population. Psychiatric Services
Morris CD et al. (in press).

Abstract

This study utilized the Colorado Client Assessment Record (CCAR) to examine predictors of tobacco use among 111,984 persons with mental illnesses receiving services in the public mental health system. Almost 39% (n = 43,508) of persons used tobacco. Multiple logistic regression analysis found that schizophrenia, schizoaffective disorder, bipolar disorder (p<.001), and depression (p<.01) were associated with greater tobacco use than other diagnoses. Significant differences in tobacco use existed across gender, age group, ethnicity, and substance use categories. Findings suggest that an administrative database is a low-burden means of identifying persons at high risk for tobacco use to inform resource allocation.

Predictors of Tobacco Use among Persons with Mental Illnesses for a Statewide Population

The 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions suggested that approximately 7.1% of the U.S. population has a psychiatric illness but consumes over 34.2% of all cigarettes (1). Forty-one percent (41%) of persons in the U.S. who reported having recent mental illnesses also smoked cigarettes based on National Comorbidity Survey data from the early 1990s (2). This is approximately twice the prevalence of cigarette smoking among adults in the general population (3). Among persons with mental illnesses, smoking varies greatly by psychiatric diagnosis (2) and is associated with higher rates of alcohol and drug use (4). If persons with mental illnesses have multiple psychiatric diagnoses, their tobacco use is further increased (2). This vulnerable population clearly carries a disproportionate share of the burden related to tobacco use and warrants ongoing attention.

Prior study of tobacco use among persons with mental illnesses has focused on the high prevalence of use for specific diagnoses such as schizophrenia, bipolar disorder, and anxiety (5-8). There have also been several studies which employed nationally representative samples, finding elevated rates of smoking across persons with mental illnesses (1-2). To our knowledge prior research has not utilized administrative data sets to investigate tobacco rates among this population.
As an alternative to past small or population-based sampling methods, there is growing interest in utilizing large administrative databases to inform resource allocation and treatment guidelines (2). Findings from large statewide databases might complement existing findings regarding rates of tobacco use among persons with mental illnesses. Statewide estimates of tobacco use for individuals served by the public mental health system might support planning for primary and secondary intervention approaches, suggest potential barriers, and serve as a benchmark for future outcomes and research.

The objectives of this study are to utilize the Colorado Client Assessment Record (CCAR) to estimate the prevalence of tobacco use among persons with mental illnesses, and determine the relationships between tobacco use and primary diagnosis (i.e., schizophrenia, bipolar, schizoaffective, depression/ dysthymia, anxiety, compared to all other diagnoses), and alcohol and drug use (amphetamine, barbiturates, caffeine, cocaine, marijuana, heroin, inhalants, and all other substance use)  among individuals accessing public sector mental health care in Colorado. We test the hypotheses that 1) primary diagnoses of schizophrenia, schizoaffective disorder, and bipolar disorder would be associated with highest rates of smoking, followed by depression and anxiety, and then all other diagnoses grouped together, and 2) other substance use would be associated with increased tobacco use, independent of primary diagnosis.  

METHODS

The study population included 111,984 unduplicated individuals ages 12 and older that the Colorado public mental health system served during the 2003 and 2004 fiscal years with complete data on key variables. This represents 99.6% of all cases (406 cases excluded). Data are inclusive of individuals receiving a continuum of inpatient and outpatient services.

Data were obtained from the CCAR maintained by the Colorado Division of Mental Health, which provided patient-level data stripped of individual identifiers. CCARs were required for all persons the public mental health system serves at admission, discharge and annually. Individuals were considered tobacco users if they endorsed current tobacco use on any CCAR during the study interval. Clinicians completed the CCAR data fields based on interview, treatment records, and available history. Public mental health system clinicians who collected data had a spectrum of educational backgrounds, but all were required to complete standardized CCAR training.

We used SPSS (Version 12.0; SPSS Inc., Chicago, Il.) for the analysis. We classified individuals by primary diagnosis; thus diagnostic categories are mutually exclusive and indicator variables are coded 1, if yes (i.e. primary diagnosis) and 0, if no, with “other? as the reference category. Substance use variables were coded 1, if present on the CCAR and 0, if not, but these do not constitute mutually exclusive categories and individuals can be positive for multiple substances. Gender (reference=male with categories for female and “unknown?), race/ethnicity (reference=white), and age group (reference=18-59) were all categorical variables. Primary diagnosis and tobacco use were available for all individuals. Categories for unknown gender and unknown race/ethnicity were included but cases with missing data on substance use were excluded from the analysis.
We inspected frequency distributions for all variables and used chi-square tests to examine bivariate relationships between tobacco use and diagnostic category, substance use, and sociodemographic characteristics. Variables that did not meet the assumptions of the chi-square test due to small cell sizes were not considered for multivariate analysis. Since the large sample size provided sufficient power to detect associations that might not be clinically significant, variables were only included in the final model if they were significantly associated with the outcome at p<.01 in chi-square tests. 

To test the hypotheses that primary diagnosis and other substance use would be independently associated with tobacco use, controlling for gender, age, and race/ethnicity we used multiple logistic regression analysis, with tobacco use as the dependent variable and all independent variables entered simultaneously. Adjusted odds ratios with 95% confidence intervals were computed for all independent variables.

This study was exempt from institutional review board approval since publicly available data with no personal identifiers were used.

RESULTS

The overall prevalence of tobacco use in the sample was 38.7% (n = 43,508). Table 1 presents the results of the multivariate logistic regression analysis. The regression model correctly classified 71.2% of cases (Nagelkerke R2 =.257). Males were more likely to report smoking tobacco than females (p<.001). There were significant differences in the smoking prevalence among age groups. Compared to adults 18 to 59 years old, adolescents were less likely to report using tobacco (adjusted OR=.37, p<.001) as were older adults (adjusted OR = .50, p<.001). Compared to the race/ethnicity reference group of Whites, American Indian/Alaska Natives were the only group more likely to use tobacco (adjusted OR=1.29, p<.001), while Asian, Native Hawaiian/Pacific Islander, and Hispanic groups were less likely to use tobacco (p<.001 for all). At the extreme, Asians were half as likely to smoke when compared to Whites (adjusted OR=.50, p<.001).There were no differences between African American or Multi-Racial groups compared to the White group.
Compared to a reference category of all other primary diagnoses, persons with diagnoses of schizophrenia, schizoaffective disorder, bipolar disorder (p<.001 for all), and depression/dysthymia (p<.01) were more likely to use tobacco, while individuals with anxiety did not differ from the “other? category. At the extreme, individuals with schizophrenia were 2.61 times and schizoaffective disorder 2.14 times more likely to use tobacco than individuals in the “other? diagnostic category.

We also examined co-occurrence of tobacco use and alcohol and other substance use for the study sample. Individuals who used alcohol, amphetamines, caffeine, cocaine, and marijuana were significantly more likely to use tobacco (p<.001 for all).

DISCUSSION

This study represents a statewide exploration of tobacco use for almost 112,000 persons with serious mental illnesses who received services from the public mental health system over the course of two years. The study’s finding that 38.7% of the sample used tobacco approximates other population based research examining the prevalence of smoking for adults with psychiatric disorders (2). This is about double the smoking rate of 20.4% for Colorado’s adult population (9).

Smoking rates for specific diagnoses were also similar to previous research; although rates for bipolar disorder (50.7%) and anxiety (32.0%) were lower than previously found rates, which were 60.6% and 46.0% respectively (2). The data support our hypothesis that primary diagnoses of schizophrenia, schizoaffective disorder, and bipolar disorder are associated with the highest rates of smoking, compared to other diagnoses. Consistent with other research, the data support our hypothesis that substance use is also associated higher rates of smoking (4). At a tobacco use rate of 30%, persons using the public mental health system with diagnoses other than schizophrenia, schizoaffective disorder, bipolar disorder, anxiety, or depression also smoked at a greater rate than the general population, which is indicative of these individuals’ generally higher psychiatric symptom burden.

This study has several limitations. The CCAR is an instrument completed in the field by mental health clinicians. Thus, the diagnostic categories and other ratings are based on data available to community-based clinicians. Much of the data are based on self-report. We also did not capture data on frequency, intensity or duration of tobacco use behaviors or mental health treatment.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the assistance provided by Debra Kupfer and Judith Butler at the Colorado Division of Mental Health.

REFERENCES

1. Grant BF, Hasin DS, Chou SP, et al: Nicotine dependence and psychiatric disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions. Archives of General Psychiatry 61: 1107-1115, 2004
2. Lasser K, Boyd JW, Woolhandler S, et al: Smoking and mental illness: a population-based prevalence study. Journal of the American Medical Association 284: 2606-2610, 2000
3. U.S. Department of Health and Human Services: Reducing tobacco use: a report of the surgeon general. 2000 [On-line], Available: www.cdc.gov/tobacco/sgr_tobacco_use.htm
4. Regier DA, Farmer ME, Rae DS, et al. Comorbidity of mental disorders with alcohol and other drug abuse. Journal of the American Medical Association 264: 2511-2518, 1990
5. Breslau N, Klein DF: Smoking and panic attacks: an epidemiologic investigation. Archives of General Psychiatry 56: 1141-1147, 1999
6. Waxmonsky JA, Thomas MR, Miklowitz DJ, et al: Prevalence and correlates of tobacco use in bipolar disorder: data from the first 2,000 participants in Systematic Treatment Enhancement Program. General Hospital Psychiatry 27: 321-328, 2005
7. Glassman AH, Helzer JE, Covio LS et al: Smoking, smoking cessation, and major depression. Journal of the American Medical Association 264: 1546-1549, 1990
8. Kelly C, McCreadie RG: Smoking habits, current symptoms, and premorbid characteristics of schizophrenic patients in Nithsdale, Scotland. American Journal of Psychiatry 156: 1751-1757, 1999
9. Colorado Department of Public Health and Environment, 2002
10. Pandiani JA, Banks SM: Large data sets are powerful. Letter to the Editor. Psychiatric Services 54, 745, 2003

CONCLUSIONS

There is little prior report of tobacco use rates and predictors of tobacco use for statewide populations accessing the public mental health system. This study furthers the work of existing small sample and nationally representative investigations by providing a cross-sectional analysis of the clinical and demographic factors associated with smoking behavior in a large community-based sample. We found that this large statewide administrative dataset presents an impressive data source which has broad relevance to the mental health community (10). By describing the predictors of tobacco use among persons with mental illnesses, study findings have assisted the state to identify priority subgroups of tobacco users such as persons with schizophrenia and persons with co-occurring mental illnesses and substance use. We found that CCAR data is a low-burden basis for service planning, policy initiatives, and ongoing tobacco use research.

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